Parietal and prefrontal: categorical differences?

Beyond Routine Maintenance: Current Trends in Working Memory Research

Working memory (WM) is an evolving concept. Our understanding of the neural functions that support WM develops iteratively alongside the approaches used to study it, and both can be profoundly shaped by available tools and prevailing theoretical paradigms. Here, the organizers of the 2024 Working Memory Symposium-inspired by this year's meeting-highlight current trends and looming questions in WM research. This review is organized into sections describing (1) ongoing efforts to characterize WM function across sensory modalities, (2) the growing appreciation that WM representations are malleable to context and future actions, (3) the enduring problem of how multiple WM items and features are structured and integrated, and (4) new insights about whether WM shares function with other cognitive processes that have conventionally been considered distinct. This review aims to chronicle where the field is headed and calls attention to issues that are paramount for future research.

Timescales of learning in prefrontal cortex

The lateral prefrontal cortex (PFC) in humans and other primates is critical for immediate, goal-directed behaviour and working memory, which are classically considered distinct from the cognitive and neural circuits that support long-term learning and memory. Over the past few years, a reconsideration of this textbook perspective has emerged, in that different timescales of memory-guided behaviour are in constant interaction during the pursuit of immediate goals. Here, we will first detail how neural activity related to the shortest timescales of goal-directed behaviour (which requires maintenance of current states and goals in working memory) is sculpted by long-term knowledge and learning - that is, how the past informs present behaviour. Then, we will outline how learning across different timescales (from seconds to years) drives plasticity in the primate lateral PFC, from single neuron firing rates to mesoscale neuroimaging activity patterns. Finally, we will review how, over days and months of learning, dense local and long-range connectivity patterns in PFC facilitate longer-lasting changes in population activity by changing synaptic weights and recruiting additional neural resources to inform future behaviour. Our Review sheds light on how the machinery of plasticity in PFC circuits facilitates the integration of learned experiences across time to best guide adaptive behaviour.

Exploring memory-related network via dorsal hippocampus suppression

Memory is a complex brain process that requires coordinated activities in a large-scale brain network. However, the relationship between coordinated brain network activities and memory-related behavior is not well understood. In this study, we investigated this issue by suppressing the activity in the dorsal hippocampus (dHP) using chemogenetics and measuring the corresponding changes in brain-wide resting-state functional connectivity (RSFC) and memory behavior in awake rats. We identified an extended brain network contributing to the performance in a spatial-memory related task. Our results were cross-validated using two different chemogenetic actuators, clozapine (CLZ) and clozapine-N-oxide (CNO). This study provides a brain network interpretation of memory performance, indicating that memory is associated with coordinated brain-wide neural activities.

Significance Statement

Successful memory processes require coordinated activity in a large-scale brain network, extending beyond a few key, well-known brain regions like the hippocampus. However, the specific brain regions involved and how they orchestrate their activity that is pertinent to memory processing remain unclear. Our study, using a chemogenetics-rsfMRI- behavior approach in awake rats, elucidates a comprehensive framework of the extended memory-associated network. This knowledge offers a broader interpretation of memory processes, enhancing our understanding of the neural mechanisms behind memory function, particularly from a network perspective.

Long-term learning transforms prefrontal cortex representations during working memory

The role of the lateral prefrontal cortex (lPFC) in working memory (WM) is debated. Non-human primate (NHP) electrophysiology shows that the lPFC stores WM representations, but human neuroimaging suggests that the lPFC controls WM content in sensory cortices. These accounts are confounded by differences in task training and stimulus exposure. We tested whether long-term training alters lPFC function by densely sampling WM activity using functional MRI. Over 3 months, participants trained on both a WM and serial reaction time (SRT) task, wherein fractal stimuli were embedded within sequences. WM performance improved for trained (but not novel) fractals and, neurally, delay activity increased in distributed lPFC voxels across learning. Item-level WM representations became detectable within lPFC patterns, and lPFC activity reflected sequence relationships from the SRT task. These findings demonstrate that human lPFC develops stimulus-selective responses with learning, and WM representations are shaped by long-term experience, which could reconcile competing accounts of WM functioning.

Categorical Biases in Human Occipitoparietal Cortex

Categorization allows organisms to generalize existing knowledge to novel stimuli and to discriminate between physically similar yet conceptually different stimuli. Humans, nonhuman primates, and rodents can readily learn arbitrary categories defined by low-level visual features, and learning distorts perceptual sensitivity for category-defining features such that differences between physically similar yet categorically distinct exemplars are enhanced, whereas differences between equally similar but categorically identical stimuli are reduced. We report a possible basis for these distortions in human occipitoparietal cortex. In three experiments, we used an inverted encoding model to recover population-level representations of stimuli from multivoxel and multielectrode patterns of human brain activity while human participants (both sexes) classified continuous stimulus sets into discrete groups. In each experiment, reconstructed representations of to-be-categorized stimuli were systematically biased toward the center of the appropriate category. These biases were largest for exemplars near a category boundary, predicted participants' overt category judgments, emerged shortly after stimulus onset, and could not be explained by mechanisms of response selection or motor preparation. Collectively, our findings suggest that category learning can influence processing at the earliest stages of cortical visual processing.SIGNIFICANCE STATEMENT Category learning enhances perceptual sensitivity for physically similar yet categorically different stimuli. We report a possible mechanism for these changes in human occipitoparietal cortex. In three experiments, we used an inverted encoding model to recover population-level representations of stimuli from multivariate patterns in occipitoparietal cortex while participants categorized sets of continuous stimuli into discrete groups. The recovered representations were systematically biased by category membership, with larger biases for exemplars adjacent to a category boundary. These results suggest that mechanisms of categorization shape information processing at the earliest stages of the visual system.

Two different mechanisms support selective attention at different phases of training

Selective attention supports the prioritized processing of relevant sensory information to facilitate goal-directed behavior. Studies in human subjects demonstrate that attentional gain of cortical responses can sufficiently account for attention-related improvements in behavior. On the other hand, studies using highly trained nonhuman primates suggest that reductions in neural noise can better explain attentional facilitation of behavior. Given the importance of selective information processing in nearly all domains of cognition, we sought to reconcile these competing accounts by testing the hypothesis that extensive behavioral training alters the neural mechanisms that support selective attention. We tested this hypothesis using electroencephalography (EEG) to measure stimulus-evoked visual responses from human subjects while they performed a selective spatial attention task over the course of ~1 month. Early in training, spatial attention led to an increase in the gain of stimulus-evoked visual responses. Gain was apparent within ~100 ms of stimulus onset, and a quantitative model based on signal detection theory (SDT) successfully linked the magnitude of this gain modulation to attention-related improvements in behavior. However, after extensive training, this early attentional gain was eliminated even though there were still substantial attention-related improvements in behavior. Accordingly, the SDT-based model required noise reduction to account for the link between the stimulus-evoked visual responses and attentional modulations of behavior. These findings suggest that training can lead to fundamental changes in the way attention alters the early cortical responses that support selective information processing. Moreover, these data facilitate the translation of results across different species and across experimental procedures that employ different behavioral training regimes.

Neural mechanisms of information storage in visual short-term memory

The capacity to briefly memorize fleeting sensory information supports visual search and behavioral interactions with relevant stimuli in the environment. Traditionally, studies investigating the neural basis of visual short term memory (STM) have focused on the role of prefrontal cortex (PFC) in exerting executive control over what information is stored and how it is adaptively used to guide behavior. However, the neural substrates that support the actual storage of content-specific information in STM are more controversial, with some attributing this function to PFC and others to the specialized areas of early visual cortex that initially encode incoming sensory stimuli. In contrast to these traditional views, I will review evidence suggesting that content-specific information can be flexibly maintained in areas across the cortical hierarchy ranging from early visual cortex to PFC. While the factors that determine exactly where content-specific information is represented are not yet entirely clear, recognizing the importance of task-demands and better understanding the operation of non-spiking neural codes may help to constrain new theories about how memories are maintained at different resolutions, across different timescales, and in the presence of distracting information.